Dive into the foundations of deep learning with this comprehensive lecture from MIT's Introduction to Deep Learning course. Explore key concepts including perceptrons, neural networks, loss functions, gradient descent, backpropagation, and regularization techniques. Learn why deep learning is revolutionizing various fields and how to apply neural networks to real-world problems. Gain insights into crucial aspects of training neural networks, such as setting learning rates and implementing batched gradient descent. By the end of this 58-minute session, acquire a solid understanding of the fundamental principles driving modern deep learning applications.